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Updated: Sep 5, 2026

Two-Photon Intravital Microscopy of Glioblastoma in a Murine Model
Published on: March 1, 2024
Integrating ex vivo platforms with AI to guide glioblastoma treatment
Mainak Bardhan1,2, Samanta Paul3, Sirjana Pun4
1The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA.
Purpose:
Ex vivo platforms can rapidly and cost-effectively screen patient-derived tumor cells or tissue. Artificial intelligence (AI) algorithms can search and identify patterns in large datasets and provide predictions. This review focuses on integrating microphysiological platforms with AI to inform physician and patient decision-making.
Methods And Results:
Combining efficacy, safety, and pharmacology results from drug screens with the output of extensive AI searches can yield insights to guide physician and patient decision-making and potentially improve a patient's prognosis. We detail ex vivo platforms at different stages of development that represent the diversity of approaches: a microphysiological system and a high-throughput screen that assesses drug cytotoxicity in both bulk and drug-tolerant tumor cells. We review AI approaches that can enhance the utility of microphysiological platforms.
Conclusion:
Integrating emerging microphysiological platforms with AI is expected to significantly impact physician and patient choice of treatment.
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10:52Stereotactic Intracranial Implantation and In vivo Bioluminescent Imaging of Tumor Xenografts in a Mouse Model System of Glioblastoma Multiforme
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